- The course introduces popular tools like Jupyter Notebooks, Git, and GitHub.
- Learners get exposure to Python and R environments for data analysis.
- Data visualization and data manipulation tools are also demonstrated.
- Emphasis is placed on practical usage and workflow integration.
- Skills learned are transferable to real-world data science projects.
